AI Strategy for Sales and Marketing: Connecting Marketing, Sales and Customer Experience

Cover
Contents
About the author
Acknowledgements
01 AI and the future of work and society
	Optimism for innovation that benefits society and business
	Roaring twenties
	The impact of machine learning
	Customer focus: smart marketing
	The personalized experience
	Driving change
	A small window of opportunity
	Is AI worthy of global attention?
	A global duty to raise living standards
	Market share
	The AI race: the US and China
	AI in the Middle East and South Asia
	AI in Europe
	Investment in AI for marketing
	AI for improved collaboration
	AI in Australia
	Beyond the pretty shiny objects
	AI is not a silver bullet for comms
	Digital twins
	Bibliography
02 Strategic AI tools for marketing, sales and CX
	Which tools are available?
	Replicate human reasoning
	AI and events
	Emotionally intelligent chatbots
	Start with what you know
	Accessible for smaller budgets
	Minimizing daily minutiae in customer service, sales, HR and marketing
	Smarter social listening
	Examples from hospitality
	The human side of AI
	Replacement versus reshaping
	Predicting customer needs at scale
	AI-enabled marketing automation
	Connecting marketing, sales and CX for long-term advantage
	The new AI sales landscape
	Comm tech and decision augmentation
	Move up the food chain to strategy
	AI-powered reputation-based decision-making
	Bibliography
03 How AI is reshaping the world of retail and hospitality
	Really intelligent retail
	The digital imperative
	The rise of me-commerce
	Elevating customer experiences
	Driving the future of work: intelligent marketing
	Reshaping digital marketing
	How can AI support sales?
	Bibliography
04 Driving change in the automotive and manufacturing sectors
	Building trust: AI-powered CX at Kia Motors
	Conversational AI drives empathy
	Decision Intelligence: making sense of data
	Everything as a service
	AI in manufacturing
	The environmentally conscious consumer
	The Rolls-Royce Aletheia Framework™
	Trustworthy AI isn’t necessarily good AI
	Bibliography
05 Optimizing AI data insights in finance, law and insurance
	Unlocking trust: using AI to develop a mutual relationship between bank and customer
	Conversational agents for customer support
	How to create an AI customer service platform
	Business banking
	Fraud and compliance
	Challenging the status quo
	Where next?
	How to up-tech your institution for the future
	How to get started with AI in insurance
	The UK insurance sector today
	A snapshot of the industry
	Underwriting: measuring risk
	Policy pricing
	Assessing claims
	Cutting fraud
	New business acquisition
	How insurers can use AI in their marketing and sales
	The rise of insurtech: friend or foe?
	Last but not least, people
	How is AI reshaping the legal profession?
	Bibliography
06 Revolutionizing customer support in the telecoms sector
	Six core benefits of AI for telcos
	Customer-centricity: the defining factor
	Bibliography
07 New economic model for the robot revolution
	Lifelong learning and quaternary education
	Personalized, lifelong learning
	Societal and corporate responsibility
	Education and equality
	Educating the next generation
	Enhancing education with strategic technology
	Looking ahead at learning
	AI lacks emotional attachment
	Will robots replace creativity in a work setting?
	Bibliography
08 A framework for AI success
	Strategy
	Time
	Augmentation
	Need
	Data
	Agile
	Resources
	Digital
	Investment
	Standards
	Ethics
	Industry views on AI strategy
	Business culture
	Treat AI as an assistant, not a boss
	Culture change
	Trust cleans the data
	Bibliography
09 Flourish or self-destruct?
	A fork in the road
	Regulation and compliance enforcement
	AI in the United States, under Joe Biden
	Global citizen views of AI
	AI won’t replace great human leaders
	Amplifying inequality
	Lack of oversight and measurement
	Avoid limiting AI acceleration
	Responsible citizenship: a view from the United Arab Emirates
	North America’s approach to AI issues
	Data security: a view from Canada
	Concerning knowledge gaps
	Transition from lab to real world
	The implications of AI in education
	Avoiding a digital divide
	Purpose
	A four-day working week
	Digital Darwinism in the 2020s
	Hybrid workforce
	Next gen AI: unsupervised learning
	Misuse of algorithms
	Landmark ruling: Deliveroo algorithm judged to be discriminatory
	AI might widen the gap between rich and poor
	Explainability and trust
	AI as a force for good
	The battle for AI dominance
	Respecting human rights
	Looking ahead to 2030
	Bibliography
Index